Doctors are spending 34% to 55% of their time at work analyzing medical records and taking notes. This is valuable time that could be dedicated to patients. According to experts, it costs $90 to $140 billion in physician time in one year. This is why the role of artificial intelligence in healthcare documentation is critical.
The role of artificial intelligence in healthcare documentation is becoming more and more popular. It is currently being used across various hospital settings. But, not everywhere. The question is, what can AI offer our healthcare system. Is it really that important? Here is my take on AI use in the healthcare industry.
Relevant Types of Artificial Intelligence in Healthcare Documentation
- The burnout rate among clinicians is about 44%. That means doctors have a much higher burnout rate compared to any other profession. Their burnout is often linked with the demanding administrative and reporting workload.
It is imperative to alter the design and way in which we use electronic medical records (EHRs). In fact, it is in dire need of a complete overhaul. That’s where artificial intelligence can make a solid impact.
AI is not single tech but a collection of technologies. These algorithms can outperform many aspects of documentation and specific tasks. The healthcare system can utilize this technology to create data compliance and integrity. As well as better workflow and a value-based care model.
When we embrace AI in our current healthcare system, we can define our capability to provide better service and health outcomes. Estimated data shows that the global artificial intelligence market in healthcare is expected to expand dramatically.
If healthcare documentation is done properly, it can ease the burden on doctors and improve patient care. If you do it right, AI can take care of the administrative duties and free up some valuable time.
Still not convinced? Here are some of the most important types of artificial intelligence in healthcare documentation.
Machine Learning (ML)
Based on a 2018 survey, 63% of companies already implemented forms of machine learning. In healthcare, this is precision medicine. It can predict the most viable treatment protocol that can help patients.
With applications such as these, it becomes much easier to select the best form of treatment based on the patient’s attributes and health state. In other words, AI makes for a practical choice for coming up with a solid diagnosis and treatment applications.
Natural Language Processing (NLP)
AI contributes to better accuracy of recognition. In healthcare, it can help classify and understand published research and clinical documentation. NLP systems can assess unstructured clinical patient notes, prepare examinations, reports, and transcribe patient interaction.
Based on studies, AI has better odds of automating and capturing the process of analyzing and manipulating information. It has a superior capability in comparing, searching, collecting, and analyzing data compared to a human.
What Could AI Accomplish That We Haven’t Done So Far?
In the last decade, there has been a surge of healthcare data available to everyone. For instance, more than 11,000 dermatology articles get published every single year. And people are eager to read health-related content that would help them manage their health state.
Besides, AI and ML have already provided value in certain areas. A survey found that artificial intelligence in telehealth is quite impactful. Here is how the statistics looked like.
Perceived value of people who agree that AI and ML are useful in Telehealth
Delivers value in specialty care (e.g., pharma, pathology, radiology)
Delivers value at the bedside
Delivers value for the patient (e.g., remote health monitoring)
From my point of view, some chronic health conditions will benefit more from AI or ML. Such as infectious diseases, neurological complications, heart problems, and diabetes. Experts are using this technology to come up with new ways and tools to battle these conditions.
With the constantly evolving technological advances, it is no wonder why scientists keep finding new ways to improve the healthcare system. But, the exponential growth also makes it difficult to stay on track.
Artificial intelligence provides a solid data structure. It helps you stay up to date and gives you immediate access to any information you like.
The same thing can be said with healthcare products. New solutions, formulas, and better medicine are created now more than ever. Without AI, almost 80% of that data can remain unstructured. Without structure, you can’t really put it to good use.
But, tech can go way beyond these developments in healthcare documentation. Now, it is about taking it a step further by using augmented, virtual reality, and robotics. This provides a focus on preventative and collaborative care.
Technology gives access to remarkable AI tools that are already a part of mobile devices, such as iOS and Android, which lead to better democratization of healthcare access. We have wearable devices that enable access to valuable data and analytics. With it, people can proactively take control of their well-being and health. They can also make better decisions. In other words, simple and effective.
Final Thoughts on The role of Artificial Intelligence in Healthcare Documentation
AI can help the healthcare documentation system in more ways than one. It is a great option for enhancing the doctor’s ability to ensure adequate patient care. But, most importantly, it can ease their cognitive workload and boost care coordination. This is something the field can greatly benefit from, especially now, with the COVID pandemic and the high numbers of patients in need of care.
As you can see, AI wouldn’t be that good if it didn’t have some additional benefits. After analyzing the data and statistics, I came to realize that artificial intelligence offers some exceptional configurability and modularity. This is something that can be used in the long run—especially when dealing with the current burnout issue happening in many hospitals.
What do you think of the role of Artificial intelligence in healthcare documentation? Will further improvement and incorporation lead to a better outcome? I would love to know what you think. Share your thoughts in the comment section below!